The building sector accounts for over 40% of global energy consumption, and many buildings are old and inefficient. However, the current pace of building renovation is not sufficient to make a tangible impact. A new strategy is needed to accelerate the renovation process. Renovation at the district level and the use of digital tools, such as a digital twin (DT) of a city district, can provide a solution. This paper proposes a novel approach to city block renovation using renewable energy sources (RES), including photovoltaic (PV) solar panels, heat pumps (HP), and electric heaters (EH), while utilizing a DT of a city district to provide a user-friendly representation of the results and data needed for holistic solutions. The proposed method combines an optimization model of the optimal heating system with a solar PV simulation technique to analyse hybrid RES solutions and potential on-site energy generation and supply. Several scenarios are simulated to evaluate RES solutions in the renovation process of the city block using the DT concept. The simulation results demonstrate that a hybrid RES solution, which includes a PV system and a heating system, is optimal when the on-site generated energy is used not only for domestic electricity consumption, but also for the operation of HPs and EHs for heat generation. This study highlights the importance and significance of a DT approach to city block renovation and provides a new solution to accelerate the renovation process and reduce energy consumption in the building sector.

District heating systems are gaining global recognition as an essential tool for reducing greenhouse gas emissions and transitioning to a low-carbon-energy future. In this context, heat pumps are becoming an important technology, providing an effective solution for improving energy efficiency and reducing the reliance on fossil fuels in heating systems. Therefore, this study is focused on the optimal selection of heat pump systems for different types of buildings considering technical, economic, environmental, and social factors. This paper proposes a novel methodology based on mixed-integer nonlinear programming and multi-objective optimization that minimizes total costs and reduces CO₂ emissions for heat production and supply systems over a desired period. The methodology is applied to various building types, including renovated and unrenovated apartment buildings, schools, kindergartens, and a supermarket. The study analyzes various types of heat pumps and electric heaters for space heating and domestic hot water production. Optimization results showed that the optimal heating system includes air-to-water heat pumps and electric heaters. Furthermore, for schools and a supermarket, these systems are combined with hybrid heat pumps. The goal of making the heating system neutral in terms of CO₂ emissions was achieved for eight out of eleven buildings analyzed. The most profitable investments were in the heating systems of renovated five-story and unrenovated nine-story apartment buildings due to their low energy costs (0.0831 EUR/kWh), short payback periods, and high returns on investment.